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Disclosed is a method for predictive/automatic high risk intoxication detection and risk notification using voice biometric, Internet of Things (IoT) and Analytics Delta over

wireless network.

It has been reported that in 2006, 25% of people aged 15 to 20 who were killed in motor

vehicle accidents had been drinking alcohol. The Centers for Disease Control and Prevention (CDC) reports that drivers, ages 16-20, are 17 times more likely to die in a crash when they have a blood alcohol concentration of .08% than when they have not been drinking. The CDC estimates that more than one million high school teens drank alcohol and got behind the wheel in 2011. To detect blood alcohol levels, alcohol vapor detection as well as laser detection on alcohol vapor are utilized. The limitations of this type of detection is the requisite physical closeness to the persons trying to detect. There is a device available now that detects alcohol levels by building vapor detection into the phone; however, if a person isn't on the phone, it cannot detect alcohol levels.

The disclosed method utilizes the internet coupled with IoT networks and social networks to automatically track the user's risk of getting drunk. Upon detection of the higher risk, a speech module in the connected car will be triggered when the driver tries to start the engine. A few psychological and memory questions are asked to confirm

the driver's fitness for driving the car. If deemed not fit, proper notification is sent through automated communications such as email and phone contact.

The primary advantage is that the user is unconsciously (unaware) monitored and potential drunk driving can be detected before starting the car engine, which could